Senior Solution Architect

Senior Solution Architect – Applied AI (Dubai, Onsite)

Category: Digital Engineering – Cloud Native Development

About the Role

We are seeking a Senior Solution Architect to lead Applied AI initiatives across the enterprise. You will anchor how LLM and agentic AI capabilities are designed, built, and deployed, working hands-on with code, frameworks, and stakeholders. This is a technical leadership role requiring both architectural vision and practical engineering depth.

Responsibilities

• Partner with stakeholders to translate business problems into technical solutions.
  

• Own end-to-end solution architecture for LLM and agentic systems (orchestration, retrieval pipelines, MCP integrations, tool design).
  

• Build working prototypes to validate designs before full-scale implementation.
  

• Continuously evaluate emerging AI platforms, frameworks, and models.
  

• Lead and mentor Applied AI engineers, setting technical direction and standards.
  

• Establish engineering practices for observability, evaluation, release, and compliance.
  

• Collaborate with IT Security, Data Governance, and Legal to ensure scalable, auditable solutions.
  

Required Skills & Experience

• 10+ years in technical roles (Solutions Architect, Technical Lead, Senior Engineer).
  

• Hands-on experience delivering LLM/agentic AI solutions to production (not just PoCs).
  

• Strong enterprise integration background (APIs, event-driven patterns, pipelines, cloud architecture).
  

• Proficiency in Python plus one additional language (TypeScript, C#, or Java).
  

• Familiarity with:
  

  • Cloud AI Platforms: Azure AI Foundry, Azure OpenAI, AWS Bedrock, Google Vertex AI
    

  • Agent Tooling: Copilot Studio, Power Platform, Power Automate, Azure AI Agent Service
    

  • Frameworks: LangGraph, Semantic Kernel, OpenAI Agents SDK, Claude Agent SDK, Pydantic AI
    

  • Retrieval & Knowledge: Azure AI Search, pgvector, LlamaIndex, GraphRAG, Neo4j, Qdrant, Pinecone
    

  • Evaluation & Observability: Promptfoo, DeepEval, Ragas, LangSmith, Langfuse, Azure AI Evaluation
    

  • Engineering Tools: FastAPI, React, Docker, Kubernetes, Azure DevOps, GitHub Actions
    

  • Data Platforms: SQL, Kafka/Event Hubs, Databricks/Fabric, Snowflake
    

• Experience in security-conscious or regulated environments.
  

• Strong stakeholder management skills (engineers + executives).
  

• Machine learning/data science background is a plus.